Bioinformatics and Multi-Omics-Driven Algal Systems Biology for Environmental and Biotechnological Applications

Obaid Ur Rehman; Muhammad Tayyab; Wei Liu; Shijiang Cao; Xinjuan Hu; Muhammad Uzair; Feifei Zhu; Shuhao Huo

doi:10.53941/algaeenviron.2025.100007

Abstract

Significant improvement in bioinformatics and integrated multi-omics technologies that enable interrogation of biological complexity on the system level to advance algal research. Genomic analyses provide a foundational blueprint that enables the production of high-quality genomes and the identification of genes responsible for desirable characteristics, such as high lipid production and stress resilience. Transcriptomic profiling also describes the dynamics of gene expression, thereby explaining the regulatory networks that control key pathways, including photosynthesis and carbon partitioning. Proteomic analyses map the functional proteome and essential post-translational adaptations, whereas the study of endogenous small molecules by metabolomics can map metabolic flux and verify the rate-limiting step. This strong combination of heterogeneous data, facilitated by computational pipelines, enables the reconstruction of genome-scale metabolic models, which in turn facilitate the prediction of metabolic fluxes and the identification of strategic engineering leverage points. These efforts are complemented by machine-learning methods that identify subtle trends in large datasets to enhance gene annotation, predict gene behavior, and optimize cultivation in silico. Together, these bioinformatics-based procedures can provide an exceptional and widespread understanding of algal physiology. This systems-biology platform will expedite the rational design and development of engineered algal strains, thereby streamlining the use of algal strains for the generation of sustainable biofuels, high-value bioproducts, and industrial biotechnology.

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